Cancer Missense Mutations Alter Binding Properties of Proteins and Their Interaction Networks

• Published in: PloS one Vol. 8; no. 6; p. e66273
• Main Authors: Nishi, Hafumi, Tyagi, Manoj, Teng, Shaolei, Shoemaker, Benjamin A., Hashimoto, Kosuke, Alexov, Emil, Wuchty, Stefan, Panchenko, Anna R.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 14.06.2013; Public Library of Science (PLoS)
• Subjects: Acids; Amino acid sequence; Amino acids; Analysis; Artificial Intelligence; Binding Sites; Bioinformatics; Biology; Biomarkers; Biophysics; Biotechnology; Brain cancer; Cancer; Carcinogenesis; Carcinogens; Chemical properties; DNA-Binding Proteins - chemistry; DNA-Binding Proteins - genetics; DNA-Binding Proteins - metabolism; Energy (Physics); Genes; Genomes; Glioblastoma; Glioblastoma - genetics; Glioblastoma - metabolism; Gliomas; Humans; Interfaces; Medicine; Missense mutation; Models, Biological; Mutation; Mutation, Missense; National libraries; Nervous system; Network analysis; Nucleic acids; Phenotype; Physicochemical properties; Protein Binding; Protein Interaction Domains and Motifs - genetics; Protein Interaction Maps; Protein Stability; Proteins; Thermodynamics; Transduction; Turnover rate; United States > US; Maryland; South Carolina
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0066273

Many studies have shown that missense mutations might play an important role in carcinogenesis. However, the extent to which cancer mutations might affect biomolecular interactions remains unclear. Here, we map glioblastoma missense mutations on the human protein interactome, model the structures of affected protein complexes and decipher the effect of mutations on protein-protein, protein-nucleic acid and protein-ion binding interfaces. Although some missense mutations over-stabilize protein complexes, we found that the overall effect of mutations is destabilizing, mostly affecting the electrostatic component of binding energy. We also showed that mutations on interfaces resulted in more drastic changes of amino acid physico-chemical properties than mutations occurring outside the interfaces. Analysis of glioblastoma mutations on interfaces allowed us to stratify cancer-related interactions, identify potential driver genes, and propose two dozen additional cancer biomarkers, including those specific to functions of the nervous system. Such an analysis also offered insight into the molecular mechanism of the phenotypic outcomes of mutations, including effects on complex stability, activity, binding and turnover rate. As a result of mutated protein and gene network analysis, we observed that interactions of proteins with mutations mapped on interfaces had higher bottleneck properties compared to interactions with mutations elsewhere on the protein or unaffected interactions. Such observations suggest that genes with mutations directly affecting protein binding properties are preferably located in central network positions and may influence critical nodes and edges in signal transduction networks.